Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 201 20 640 135 151 804 722 10 873 333 204 84 213 350 830 623 234 969 484 502
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 830 502 10 969 84 204 333 NA 804 NA 640 350 213 151 722 234 135 873 NA 20 623 201 484
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 1 4 2 1 1 3 3 1 4 3
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "d" "p" "r" "v" "k" "U" "T" "I" "F" "R"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 18
which( manyNumbersWithNA > 900 )
[1] 4
which( is.na( manyNumbersWithNA ) )
[1] 8 10 19
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 969
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 969
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 969
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "U" "T" "I" "F" "R"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "d" "p" "r" "v" "k"
manyNumbers %in% 300:600
[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE FALSE FALSE FALSE
[18] FALSE TRUE TRUE
which( manyNumbers %in% 300:600 )
[1] 10 14 19 20
sum( manyNumbers %in% 300:600 )
[1] 4
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "large" "large" "small" "large" "small" "small" "small" NA "large" NA "large" "small" "small"
[14] "small" "large" "small" "small" "large" NA "small" "large" "small" "small"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "large" "large" "small" "large" "small" "small" "small" "UNKNOWN" "large" "UNKNOWN"
[11] "large" "small" "small" "small" "large" "small" "small" "large" "UNKNOWN" "small"
[21] "large" "small" "small"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 830 502 0 969 0 0 0 NA 804 NA 640 0 0 0 722 0 0 873 NA 0 623 0 0
unique( duplicatedNumbers )
[1] 1 4 2 3
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 1 4 2 3
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 4
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 969
which.min( manyNumbersWithNA )
[1] 3
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 10
range( manyNumbersWithNA, na.rm = TRUE )
[1] 10 969
manyNumbersWithNA
[1] 830 502 10 969 84 204 333 NA 804 NA 640 350 213 151 722 234 135 873 NA 20 623 201 484
sort( manyNumbersWithNA )
[1] 10 20 84 135 151 201 204 213 234 333 350 484 502 623 640 722 804 830 873 969
sort( manyNumbersWithNA, na.last = TRUE )
[1] 10 20 84 135 151 201 204 213 234 333 350 484 502 623 640 722 804 830 873 969 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 969 873 830 804 722 640 623 502 484 350 333 234 213 204 201 151 135 84 20 10 NA NA NA
manyNumbersWithNA[1:5]
[1] 830 502 10 969 84
order( manyNumbersWithNA[1:5] )
[1] 3 5 2 1 4
rank( manyNumbersWithNA[1:5] )
[1] 4 3 1 5 2
sort( mixedLetters )
[1] "d" "F" "I" "k" "p" "r" "R" "T" "U" "v"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 6.0 7.0 8.0 3.0 3.0 3.0 9.5 9.5 3.0 3.0
rank( manyDuplicates, ties.method = "min" )
[1] 6 7 8 1 1 1 9 9 1 1
rank( manyDuplicates, ties.method = "random" )
[1] 6 7 8 2 3 1 9 10 4 5
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.0000000 -0.5000000 0.0000000 0.5000000 1.0000000 -0.1466912 0.6080916 -0.5809267 1.8792200
[10] 0.8826765 0.2094058 0.2844809 -0.1942768 -0.9692771 -1.3449799
round( v, 0 )
[1] -1 0 0 0 1 0 1 -1 2 1 0 0 0 -1 -1
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 -0.1 0.6 -0.6 1.9 0.9 0.2 0.3 -0.2 -1.0 -1.3
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 -0.15 0.61 -0.58 1.88 0.88 0.21 0.28 -0.19 -0.97 -1.34
floor( v )
[1] -1 -1 0 0 1 -1 0 -1 1 0 0 0 -1 -1 -2
ceiling( v )
[1] -1 0 0 1 1 0 1 0 2 1 1 1 0 0 -1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 x 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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